Real-time validation of a robust MGOA-Tuned Sliding Mode Controller for load frequency control in a DG-integrated nonlinear power system

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10259183" target="_blank" >RIV/61989100:27240/25:10259183 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27730/25:10259183

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2352484725007450" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2352484725007450</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.egyr.2025.12.006" target="_blank" >10.1016/j.egyr.2025.12.006</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Real-time validation of a robust MGOA-Tuned Sliding Mode Controller for load frequency control in a DG-integrated nonlinear power system

Popis výsledku v původním jazyce

The growing integration of renewable distributed generators (DGs) poses significant frequency regulation challenges due to intermittency, uncertainties, and delays. This paper addresses these issues by designing and validating a robust Sliding Mode Controller (SMC) for Load Frequency Control (LFC) in complex power networks. The proposed control framework addresses a realistic multi-area system model incorporating nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB), and boiler dynamics, along with diversified generation units including thermal, hydro, gas, wind, solar photovoltaic, geothermal, and diesel-based DGs. To eliminate the chattering effect inherent in traditional SMC implementations, a saturation function is incorporated into the discontinuous control term. The SMC gains are optimally tuned using the Gannet Optimization Algorithm (GOA)-a novel bio-inspired technique modeled on the prey-capture dynamics of seabirds. Furthermore, a Modified GOA (MGOA) is proposed, where key parameters, such as the mass and velocity of gannets, are dynamically optimized using Particle Swarm Optimization (PSO) to enhance convergence precision. The comparative performance of GOA and MGOA is rigorously evaluated using six benchmark functions (e.g., Beale, Trid, Shekel), where MGOA consistently exhibits lower standard deviations and faster convergence rates, confirming its superiority in solution stability. Simulation studies conducted on MATLAB/Simulink reveal that the MGOA-SMC controller achieves superior transient performance compared to both PID and GOA-tuned SMC designs. Specifically, under a 1 % load disturbance, the proposed controller reduces frequency undershoot in area-1 from - 0.7142 x 10-3Hz to -0.2678 x 10-3 Hz with an improvement of 62.5 %, overshoot in area-1 from 0.1627 x 10-3Hz to0.0315 x 10-3 Hz with an improvement of 80.6%, and settling time from 0.15 sec to 0.02 sec with an improvement of 86.67 %. Similarly, tie-line power deviation in area-1 under the same load condition as improved by the proposed controller, such as undershoot from - 0.2378 x 10-3p.u.MW to 0.0725 x 10-3p.u.MW with an improvement of 69.5 %, overshoot from 0.0543 x 10-3p.u.MW to 0.0267 x 10-3p.u.MW with an improvement of 50.8 %, and settling time from 0.06 sec to 0.02 sec with an improvement of 66.67 %. Robustness is further validated under scenarios involving nonlinearities, a 5-millisecond communication delay, random load variations, and +/- 20 % parameter perturbations, with minimal degradation in dynamic response. The sensitivity analysis confirms low standard deviation across performance indices, reinforcing the robustness of the control strategy. The standard deviation of undershoot, overshoot, and settling time for frequency in area-1 are (0.00065), (0.000084), and (1.85), respectively. Similarly, the standard deviation of undershoot, overshoot, and settling time for tie-line power are (0.00016), (0.00079), and (2.11), respectively. To demonstrate practical viability, the proposed system is implemented on an OPAL-RT 4510 real-time simulator. Hardware-in-the-loop results closely mirror the simulation outcomes, thereby validating the controller&apos;s effec-tiveness in real-world environments. The study conclusively establishes that the MGOA-optimized SMC controller offers a scalable, computationally efficient, and resilient solution for load frequency regulation in nonlinear, DG-rich power systems. The proposed framework lays the groundwork for future extensions to address cyber-physical threats and decentralized control in smart grid applications.

Název v anglickém jazyce

Real-time validation of a robust MGOA-Tuned Sliding Mode Controller for load frequency control in a DG-integrated nonlinear power system

Popis výsledku anglicky

The growing integration of renewable distributed generators (DGs) poses significant frequency regulation challenges due to intermittency, uncertainties, and delays. This paper addresses these issues by designing and validating a robust Sliding Mode Controller (SMC) for Load Frequency Control (LFC) in complex power networks. The proposed control framework addresses a realistic multi-area system model incorporating nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB), and boiler dynamics, along with diversified generation units including thermal, hydro, gas, wind, solar photovoltaic, geothermal, and diesel-based DGs. To eliminate the chattering effect inherent in traditional SMC implementations, a saturation function is incorporated into the discontinuous control term. The SMC gains are optimally tuned using the Gannet Optimization Algorithm (GOA)-a novel bio-inspired technique modeled on the prey-capture dynamics of seabirds. Furthermore, a Modified GOA (MGOA) is proposed, where key parameters, such as the mass and velocity of gannets, are dynamically optimized using Particle Swarm Optimization (PSO) to enhance convergence precision. The comparative performance of GOA and MGOA is rigorously evaluated using six benchmark functions (e.g., Beale, Trid, Shekel), where MGOA consistently exhibits lower standard deviations and faster convergence rates, confirming its superiority in solution stability. Simulation studies conducted on MATLAB/Simulink reveal that the MGOA-SMC controller achieves superior transient performance compared to both PID and GOA-tuned SMC designs. Specifically, under a 1 % load disturbance, the proposed controller reduces frequency undershoot in area-1 from - 0.7142 x 10-3Hz to -0.2678 x 10-3 Hz with an improvement of 62.5 %, overshoot in area-1 from 0.1627 x 10-3Hz to0.0315 x 10-3 Hz with an improvement of 80.6%, and settling time from 0.15 sec to 0.02 sec with an improvement of 86.67 %. Similarly, tie-line power deviation in area-1 under the same load condition as improved by the proposed controller, such as undershoot from - 0.2378 x 10-3p.u.MW to 0.0725 x 10-3p.u.MW with an improvement of 69.5 %, overshoot from 0.0543 x 10-3p.u.MW to 0.0267 x 10-3p.u.MW with an improvement of 50.8 %, and settling time from 0.06 sec to 0.02 sec with an improvement of 66.67 %. Robustness is further validated under scenarios involving nonlinearities, a 5-millisecond communication delay, random load variations, and +/- 20 % parameter perturbations, with minimal degradation in dynamic response. The sensitivity analysis confirms low standard deviation across performance indices, reinforcing the robustness of the control strategy. The standard deviation of undershoot, overshoot, and settling time for frequency in area-1 are (0.00065), (0.000084), and (1.85), respectively. Similarly, the standard deviation of undershoot, overshoot, and settling time for tie-line power are (0.00016), (0.00079), and (2.11), respectively. To demonstrate practical viability, the proposed system is implemented on an OPAL-RT 4510 real-time simulator. Hardware-in-the-loop results closely mirror the simulation outcomes, thereby validating the controller&apos;s effec-tiveness in real-world environments. The study conclusively establishes that the MGOA-optimized SMC controller offers a scalable, computationally efficient, and resilient solution for load frequency regulation in nonlinear, DG-rich power systems. The proposed framework lays the groundwork for future extensions to address cyber-physical threats and decentralized control in smart grid applications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

<a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Energy Reports

ISSN

2352-4847

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

1-20

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

20

Strana od-do

5340-5359

Kód UT WoS článku

001636874700001

EID výsledku v databázi Scopus

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